Research on Face Aging Synthesis Based on Hybrid Domain Attention Mechanism GAN Network

Facial aging synthesis refers to the rendering of young people’s facial images from an aesthetic point of view by adding wrinkles, eye bags, stains, or changing hair color, so that they can finally show the effect of natural facial aging. Facial aging synthesis needs to consider both the authenticity of the aging effect and the consistency of identity information. The authenticity of the aging effect is based on the accurate expression of aging characteristics and the clarity of aging details. The consistency of identity information means that during the aging process, the aging face needs to maintain a certain similarity with the original young face in terms of feature information. Based on the above two issues and the instability of GAN training, this paper proposes a face aging method based on the hybrid domain attention mechanism to generate an anti-network. A large number of experiments show that this method can synthesize aging human face while ensuring the aging effect and the requirements of identity information.